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Published May 20, 2022 | Published + Accepted Version
Journal Article Open

Generating Stellar Obliquity in Systems with Broken Protoplanetary Disks

Abstract

Recent advances in submillimeter observations of young circumstellar nebulae have opened an unprecedented window into the structure of protoplanetary disks that has revealed the surprising ubiquity of broken and misaligned disks. In this work, we demonstrate that such disks are capable of torquing the spin axis of their host star, representing a hitherto unexplored pathway by which stellar obliquities may be generated. The basis of this mechanism is a crossing of the stellar spin precession and inner disk regression frequencies, resulting in adiabatic excitation of the stellar obliquity. We derive analytical expressions for the characteristic frequencies of the inner disk and star as a function of the disk gap boundaries and place an approximate limit on the disk architectures for which frequency crossing and the resulting obliquity excitation are expected, thereby illustrating the efficacy of this model. Cumulatively, our results support the emerging consensus that significant spin–orbit misalignments are an expected outcome of planet formation.

Additional Information

© 2022. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 2021 August 31; revised 2022 February 16; accepted 2022 March 4; published 2022 May 23. We would like to thank our referee, Rosemary Mardling, whose thoughtful insights significantly improved this work. J.C.B. has been supported by the Heising-Simons 51 Pegasi b postdoctoral fellowship. M.E.M. is supported by the Graduate Fellowship for STEM Diversity. This research is based in part upon work supported by NSF grant AST 2109276. K.B. thanks the David and Lucile Packard Foundation for their generous support. Software: pandas (McKinney 2010), IPython (Pérez & Granger 2007), matplotlib (Hunter 2007), scipy (Virtanen et al. 2020), numpy (Harris et al. 2020), Jupyter (Kluyver et al. 2016), Mathematica (Wolfram Research, Inc. 2020).

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Published - Epstein-Martin_2022_ApJ_931_42.pdf

Accepted Version - 2203.04429.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 24, 2023